Editorial Type:
Article
Article Type:
Research Article

Simultaneous Observations of Aerosol and Cloud Droplet Size Spectra in Marine Stratocumulus

Richard J. Vong College of Oceanic and Atmospheric Sciences, Oregon State University, Corvallis, Oregon

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David S. Covert Department of Atmospheric Sciences, University of Washington, Seattle, Washington

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Print Publication:
01 Jun 1998
DOI:
https://doi.org/10.1175/1520-0469(1998)055<2180:SOOAAC>2.0.CO;2
Page(s):
2180–2192
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Abstract

Simultaneous field measurements of aerosol and cloud droplet concentrations and droplet diameter were performed at a maritime site on the coast of Washington State. The aerosol and droplet spectra were compared for estimating cloud condensation nucleus concentration (Nccn) as the number of particles with diameters greater than 80 nm, that is, Nccn ≡ N(Dp > 80 nm). Several analytical approaches were developed and applied to the data, including a stratification of the observations into periods of high and low liquid water content (LWC) based on a threshold value of 0.25 g m−3. The aerosol data were corrected for inertial losses of cloud droplets at the inlet using wind speed and droplet size; this correction improved the measured relationships between Nccn and droplet number concentration (Nd). These measurements, when coupled with the range of possible aerosol chemical compositions, imply a cloud supersaturation of 0.24%–0.31% at the Cheeka Peak sampling site during periods of high LWC.

The observations of droplet and aerosol spectra supported Twomey’s cloud brightening hypothesis in that Nccn was highly correlated (r2 = 0.8) with Nd in apparent 1:1 proportions. For the investigated range (50 cm−3 < Nd < 600 cm−3) droplet effective diameter (Deff) was very sensitive to variation in Nccn for 50 cm−3 < Nccn < 200 cm−3, somewhat sensitive for 200 cm−3 < Nccn < 400 cm−3, but not very sensitive to variation in aerosol number for Nccn > 400 cm−3. A model was applied to the aerosol and droplet data to predict droplet size, as Deff, from N−0.33ccn and LWC. Predicted values for Deff agreed (r2 = 0.8) with Deff determined directly from the cloud droplet spectra, suggesting that this approach should be useful in climate modeling for predicting cloud droplet size from knowledge of Nccn and LWC.

Corresponding author address: Dr. Richard Vong, COAS-AtS, Oregon State University, Corvallis, OR 97331-5503.

Abstract

Simultaneous field measurements of aerosol and cloud droplet concentrations and droplet diameter were performed at a maritime site on the coast of Washington State. The aerosol and droplet spectra were compared for estimating cloud condensation nucleus concentration (Nccn) as the number of particles with diameters greater than 80 nm, that is, Nccn ≡ N(Dp > 80 nm). Several analytical approaches were developed and applied to the data, including a stratification of the observations into periods of high and low liquid water content (LWC) based on a threshold value of 0.25 g m−3. The aerosol data were corrected for inertial losses of cloud droplets at the inlet using wind speed and droplet size; this correction improved the measured relationships between Nccn and droplet number concentration (Nd). These measurements, when coupled with the range of possible aerosol chemical compositions, imply a cloud supersaturation of 0.24%–0.31% at the Cheeka Peak sampling site during periods of high LWC.

The observations of droplet and aerosol spectra supported Twomey’s cloud brightening hypothesis in that Nccn was highly correlated (r2 = 0.8) with Nd in apparent 1:1 proportions. For the investigated range (50 cm−3 < Nd < 600 cm−3) droplet effective diameter (Deff) was very sensitive to variation in Nccn for 50 cm−3 < Nccn < 200 cm−3, somewhat sensitive for 200 cm−3 < Nccn < 400 cm−3, but not very sensitive to variation in aerosol number for Nccn > 400 cm−3. A model was applied to the aerosol and droplet data to predict droplet size, as Deff, from N−0.33ccn and LWC. Predicted values for Deff agreed (r2 = 0.8) with Deff determined directly from the cloud droplet spectra, suggesting that this approach should be useful in climate modeling for predicting cloud droplet size from knowledge of Nccn and LWC.

Corresponding author address: Dr. Richard Vong, COAS-AtS, Oregon State University, Corvallis, OR 97331-5503.

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